In this session, you learnt about various model evaluation measures, such as accuracy, sensitivity, specificity, KS statistic, etc as shown in figure 1. Then, you learnt how to validate your model on in-sample data and out-time data (unseen data). Also, for stability, you learnt and understood stability by two metrics — Variable Distributive Stability and Predictive Pattern Stability. Then, you learnt about model tracking and model recalibrating steps in detail.
You can also download the lecture notes for the logistic regression module below.
There’s also an additional module on ‘Logistic Regression Interview Questions’. Feel free to visit it anytime on this link.